As we announced a few months ago, we will be starting a new feature aimed at reviewing visualization tools. This ongoing feature will hopefully shed light on these tools and if they might fit into your workflow. In the meantime, please feel free to give your opinion on this new reviewing feature in the comments section below. Should we change any of the criteria? Are there any inaccuracies? What did we miss?

We are continuing the three-part series of online visualization tools. We started last week with a review of Swivel, and now we're moving on to the heavy hitter, IBM backed tool, Many Eyes. Started in 2005 by dataviz pioneers Martin Wattenberg and Fernanda Viégas, Many Eyes was the synthesis of their independent visualization efforts with the additional element of public participation and sharing.

We chose the evaluation criteria based on user comments from our previousposts. Additionally, Benjamin (who reviewed Swivel), Patrick, and I collaborated on refining the list and adding features we thought were compelling. We also included a list of supported charts at the end of the post.

There is an active community of visualizers and data nuts. Also, in the FAQ the team at Many Eyes seems very receptive to feedback and partnerships. Since this is not a commercial endeavour, there is no dedicated customer service channel.

Data Import Formats:

Oracle

No

SQL Server

No

Sybase

No

DB2

No

PostgreSQL

No

mySQL

No

Excel

Yes

Text

Yes

other

Anything that you can copy and paste. Many Eyes has a neat input box, essentially you paste into it and you are shown a preview. Its worked for HTML tables, Google docs, and Excel.

COMMENTS

Other features

Topic Centres. Much like a site of their own, these centres allow people to gather and talk about anything from a recent election to the financial crisis to climate change. Data sets can be collects as well as visualizations of those sets.

Live & Static Embeds. I'm sure that this feature came out of the lagging java reality. Instead of embedding a java applet into your blog, many eyes will generate a nice small PNG for your convenience.

Snapshot Commenting. As previously mentioned, Many Eyes generates PNGs, and not just a thumbnail. Their system actually allows individual snapshots of different states of the visualization. This means that if you narrow down to a specific week, add a filter, then highlight a specific point, all this will be included in your full size snapshot image. Bonus: If you comment on a visualization, it will add that state into the comments field. Forget dressing up for a personal photoshoot to develop your very best avatar shot, the data will speak for itself. Your comments are directly associated with the way you have manipulated the visualization.

Watch-lists. These are much like Ebay, but eternal. You can stay updated on your favourite visualization, or make sure you get the last word in on a debate about inflation adjustments.

Rating System for Data & Visualizations. Ratings go down as well as up. This is an all in one flagging / liking system. This means if you see some data which is inaccurate, or you just plan don't like someone's numbers, you can give them a thumbs down. Also, the best rated visualizations and sets are promoted for all to see. You can't have a community without some social currency, and I'm sure there's people out there counting their points.

Pros

Responsiveness: When loaded the Java applets provide quick zooming, highlighting, filtering, and comparison.
Community Spirit: The team is ready to adapt the platform to how the users are acting. They have adapted some sharing aspects, and its clearly on a Darwinian journey.

Cons

CPU drain: The site crashed my browser several times. The embeddable static PNG format likely arose from the fact Java applets are memory beasts.
Data vs Viz: Editing data is a separate screen from the visualization, and its tough to make the visualization fit without re-structuring the format.
No iPhone/iPad, No Chrome.

Review

Many Eyes is among the three sites up for review, and likely the older of the bunch. Though it has been around for longer, its most attractive characteristic is its unfinished state. At first glance the site looks like a mashup between a 90s style portal, and a blog with too many widgets, but don not look away just yet! From sharing, to discussions, to visualization types, Many Eyes excels at the one thing it was designed for: a community of observers interested in visual data anomalies. The features that, at times, seems cobbled together, are really a representation of how the Many Eyes team works. That is, see how people are using data to converse, then provide tools for them to do it better. In the interest of full disclosure, I have never liked Java and have always fought against the use of it on the web. I also use Chrome on a Mac, and recently an iPad, so this review has forced me back into Firefox and Safari on my MacBook. Even in a proper browser the Java applets are slow-loading and cpu-eating, though quick to react with a good processor. Clearly the site is not as customer centred as Swivel, there is no pricing plan, everything is free. This can be seen even in the login form. Though a password great than 6 characters is required, the notification is simply "you've missed some fields". Now we have got the bad news out of the way, let's see why this platform is a fan favourite. Keeping in mind the purpose of Many Eyes is to "allow the entire internet to upload data, visualize it, and talk about their discoveries with other people" we'll look at the features which allow this type of dialogue.

Many Eyes has the one thing that keeps a product fresh: an active user base. Though the appearance is lacking, and its not as sexy as most full fledged data apps, its kind of quaint. I am sure many of the features above grew out of a community need, and it will be interesting to see what new features will be adopted. No Java and no Flash on the iPad/iPhone make me excited about the possibility of a true HTML solution for visualization. The Many Eyes FAQ states they are open to submission of new visualization types, and their general attitude alludes to the possibility their up for much more... As long as you are talking to the data.

For the Purists

Colour scales make sense.
Oriented around useful comparison.
Clear outlined purpose for each chart: See relationships among data points, Compare a set of values, Track rises and falls over time, See the parts of a whole, Analyze a text, See the world.

For the Aestheticians

Pretty horrid site palette, but the charting colours are much nicer.
All in all seems like an experiment in progress, but without a graphic designer at the helm.
Much of the functionality seems mashed together, but this would show that its a project in process, and it is born out of listening to a user base, so the features are likely requested.
Despite the site design, the charts are often displays Tufte would be proud of (or at least not rip to pieces).

Patrick Keenan is a founding parter at The Movement as design studio focused on amplifying social value work. Visualization is key in understanding the complexities of social change, and something Patrick pursues with deep enthusiasm.

Kim Rees is a partner at Periscopic, a socially-conscious Information Visualization firm specializing in helping nonprofit organizations and like-minded companies convey important messages and elevate public awareness.

3 COMMENTS

Great review, I agree with your opinions! Looking forward to read about the Tableau review!

Thanks for the Review and upcomming Series! The export functionality is the main criteria to get smart visualisations into use.

Sat 24 Apr 2010 at 2:24 AM

Haymon Ried

This review is extremely helpful and I am looking forward to the one about Tableau Public. Excellent post!
Another topic that would probably be interesting is: Tips and tricks to better plot your data, like what to do when you have values of 44T and 0,5 on the same list? What visualization will render your data in the better way, etc
These 'social data analysis' websites/tools are great and they are most of the times easy to handle, I think that dealing with the data is sometimes the hard part.